1. Field of the Invention
The present invention relates to a method and a system for detecting at least one object on a road, more particularly relates to a method and a system used in a vehicle for detecting at least one object on a road.
2. Description of the Related Art
With the development of cities and the popularization of vehicles, the problem of traffic and transportation has become bigger. In recent years, the speed of increase of vehicles has been far higher than that of roads and other traffic facilities. In the meanwhile, traffic accidents occur frequently, the number of injuries has increased, and personal property has been lost dramatically. As a result, a vehicle was required to have not only good safety but also a certain degree of intelligence. In the light of this, the intelligent vehicle concept occurred. At present, research is being performed for achieving an intelligent vehicle able to carry out unattended, fully-automatic, and safe driving.
In order to fulfill the above functions, in the conventional techniques, a method is proposed in which an object approaching a vehicle of a driver (for example, a person or another vehicle) is detected by carrying out a grouping (clustering) process on the basis of a disparity map of a road surface, and then a warning message is reported to the driver, or the movement state of the driver's vehicle is auto-adjusted. In this method, it is assumed that in a three-dimensional (3D) space, points in a same object domain are adjacent to each other, and the grouping process is carried out on the basis of distances and with regard to the whole disparity map. Since the grouping process is conducted on the whole disparity map, and only two frames of results are able to be obtained in one second, the method takes time, and diminishes the efficiency of dealing with an unforeseen accident. However, the method still has practical use.
Furthermore there is also a vehicle detection and recognition system provided by the BMW™ Group Research and Technology (published in “VISIGRAPH 2010”). The system carries out vehicle detection on the basis of stereoscopic vision. In particular, first, vehicles are detected by using segmentation based on a mean shift clustering process; second, vehicle assumptions (candidates) covering the different vehicles are generated by using a U-V disparity algorithm. The processing speed in the system is 2.5 frames per second (obtained in a debug environment of a 3.2 GHz and 1 GB RAM desktop computer). Since the mean shift clustering process is utilized to divide an image, and the U-V disparity algorithm is utilized to seek an object, the system also takes time.
In addition, U.S. Pat. No. 7,729,512 B2 discloses a stereoscopic image processing method of detecting a moving object. In this method, a first image and a second image are obtained by sensing an image of a moving object from two different viewpoints by using a first imaging device and a second imaging device. Plural feature points are detected from the first image. A disparity distribution representing a disparity of each feature point is obtained by performing stereoscopic image processing using the first image and the second image. A threshold is determined for disparities in the disparity distribution. A feature point having a disparity exceeding the threshold in the disparity distribution is classified as an intra-moving-object feature point. An image area of the moving object in the first image is detected by using the intra-moving-object feature point. The method adopts a clustering approach, but the object detection based on brightness, used in the clustering approach is unreliable since a moving object having brightness being virtually the same with that of the surrounding environment cannot be detected in general. Particularly in a case where the disparity of an object is virtually the same with that of an adjacent roadside tree, the method cannot detect the object having the disparity being virtually the same with the disparity of the tree.
As a result, a method and a system able to rapidly and accurately detect at least one object on the surface of a road needs to be proposed so that it is possible to more effectively achieve the driving assistance of a vehicle, and to report a warning message before an accident, so as to improve the driving safety.